Nick’s Analysis

# Normal libraries
library(ggplot2)
theme_set(theme_minimal())
library(dplyr)
library(tidyr)
library(tidyverse)
# Libraries for mapping
library(maps)
library(ggmap)
library(RColorBrewer)
library(here)
library(patchwork)
# Libraries for interactive map
library(plotly)
library(htmlwidgets)
library(extrafont)

Reading in data

crash <- readr::read_csv('crash2016.csv')

months <- c("January","February","March","April","May","June","July",
            "August","September","October","November","December")

crash <- crash %>%
  mutate(DANGEROUS_TO_DRIVE = (ROADWAY_SURFACE_COND != "DRY"),
         MONTH_NAME = months[CRASH_MONTH]) %>%
  rename("Road Conditions" = ROADWAY_SURFACE_COND)

crash_with_injury <- crash %>%
  filter(INJURIES_TOTAL > 0)

crash_no_injury <- crash %>%
  filter(INJURIES_TOTAL == 0)

Plotting Every Crash

counties <- map_data('county')

chicago_box <- c(left = -87.936287,
            bottom = 41.679835,
            right = -87.447052,
            top = 42.000835)
chicago_map <- get_stamenmap(chicago_box, zoom = 12)

chicago_map %>%
  ggmap() +
  geom_point(data = crash_with_injury, aes(x=LONGITUDE,y=LATITUDE),size=0.2)

chicago_map %>%
  ggmap() +
  geom_point(data = crash_with_injury, aes(x=LONGITUDE,y=LATITUDE),size=0.2) +
  geom_density2d(data = crash_with_injury, aes(x=LONGITUDE,y=LATITUDE), size=0.5)

downtown_box <- c(left = -87.656248,
                  bottom = 41.862511,
                  right = -87.596938,
                  top = 41.901527)
downtown_map <- get_stamenmap(downtown_box, zoom = 14)

downtown_stadium_box <- c(left = -87.712759,
                          bottom = 41.862511,
                          right = -87.596938,
                          top = 41.957135)
downtown_stadium_map <- get_stamenmap(downtown_stadium_box, zoom = 14)

# Make pretty plot
# downtown_crash_map <- downtown_stadium_map %>%
#   ggmap() +
#   ggtitle("Car Crashes in Downtown Chicago", 
#           subtitle = "An interactive map") + 
#   scale_size(range = c(1.5,12)) +
#   geom_point(data = crash_with_injury,
#              aes(x=LONGITUDE,
#                  y=LATITUDE,
#                  size=INJURIES_TOTAL,
#                  fill=`Road Conditions`,
#                  text = paste(
#                    "Street: ", STREET_NAME, "\n",
#                    "Date: ", date, "\n",
#                    "Damage: ", DAMAGE, "\n",
#                    "Road Condition: ", `Road Conditions`, "\n",
#                    "Injuries: ", INJURIES_TOTAL,
#                    sep = ""),
#                  alpha=0.94),
#              colour="black",
#              pch=21) +
#   theme(axis.title = element_blank(),
#         legend.title = element_blank(),
#         legend.position = c(1,1),
#         plot.title = element_text(family = "Arial Black",
#                                   hjust = 0.5,
#                                   size = 20,
#                                   colour = "#5C5C5C"))
# 
# # Plot graph and make interactive with plotly
# ggplotly(downtown_crash_map, tooltip = "text") %>%
#   layout(hoverlabel=list(bgcolor="lightblue", alpha=0.8),
#          title=list(text=paste0('Car Crashes in Downtown Chicago',
#                                     '<br>',
#                                     '<sup>',
#                                     'An interactive map of crashes with injury in 2016',
#                                     '</sup>')),
#          legend = list(itemclick="toggle",
#                        xanchor="auto",
#                        yanchor="auto",
#                        borderwidth = "3",
#                        bordercolor = "#79797D",
#                        itemsizing = "constant",
#                        title = list(text=paste0('Road Conditions'),
#                                     family="Arial Black")))

# Make pretty plot
downtown_crash_map_months <- chicago_map %>%
  ggmap() +
  ggtitle("Car Crashes in Downtown Chicago", 
          subtitle = "An interactive map") + 
  scale_size(range = c(1.5,12)) +
  geom_point(data = crash_with_injury,
             aes(x=LONGITUDE,
                 y=LATITUDE,
                 fill=MONTH_NAME,
                 size=INJURIES_TOTAL,
                 text = paste(
                   "Street: ", STREET_NAME, "\n",
                   "Date: ", date, "\n",
                   "Damage: ", DAMAGE, "\n",
                   "Road Condition: ", `Road Conditions`, "\n",
                   "Injuries: ", INJURIES_TOTAL,
                   sep = ""),
                 alpha=0.94),
             colour="black",
             pch=21) +
  theme(axis.title = element_blank(),
        legend.title = element_blank(),
        legend.position = c(1,1),
        plot.title = element_text(family = "Arial Black",
                                  hjust = 0.5,
                                  size = 20,
                                  colour = "#5C5C5C"))

# Plot graph and make interactive with plotly
ggplotly(downtown_crash_map_months, tooltip = "text") %>%
  layout(hoverlabel=list(bgcolor="lightblue", alpha=0.8),
         title=list(text=paste0('Car Crashes in Chicago',
                                    '<br>',
                                    '<sup>',
                                    'An interactive map of crashes with injury in 2016',
                                    '</sup>')),
         legend = list(itemclick="toggle",
                       xanchor="auto",
                       yanchor="auto",
                       borderwidth = "3",
                       bordercolor = "#79797D",
                       itemsizing = "constant",
                       title = list(text=paste0('Month(toggle)'),
                                    family="Arial Black")))